BARC Spotlight EPM on Your Data Platform
BARC Spotlight EPM on Your Data Platform: Unlocking Flexibility & AI Κατεβάστε το αρχείο BARC Spotlight
EPM on Your Data Platform:
Unlocking Flexibility & AI
Authors: Robert Tischler, Kelley Lynn Kassa
Publication: December 2025
Provided by
EPM on Your Data Platform:
Unlocking Flexibility & AI
Authors: Robert Tischler, Kelley Lynn Kassa
Publication: December 2025
Provided by
2BARC Spotlight: EPM on Your Data Platform: Unlocking Flexibility & AI
Table of Contents
Why EPM data management has reached a breaking point ....................................................................................... 3
The cost of data duplication in planning databases ....................................................................................................... 5
Formal structures constrain AI capabilities and drive spreadsheet sprawl ............................................................ 6
Storing planning data where analytics already lives ........................................................................................................7
Shared data foundations reduce effort and accelerate action ....................................................................................7
Success requires performance, usability, and organizational commitment .......................................................... 8
About BARC..................................................................................................................................................................................... 9
About SAP .......................................................................................................................................................................................10
Table of Contents
Why EPM data management has reached a breaking point ....................................................................................... 3
The cost of data duplication in planning databases ....................................................................................................... 5
Formal structures constrain AI capabilities and drive spreadsheet sprawl ............................................................ 6
Storing planning data where analytics already lives ........................................................................................................7
Shared data foundations reduce effort and accelerate action ....................................................................................7
Success requires performance, usability, and organizational commitment .......................................................... 8
About BARC..................................................................................................................................................................................... 9
About SAP .......................................................................................................................................................................................10
3BARC Spotlight: EPM on Your Data Platform: Unlocking Flexibility & AI
Why EPM data management has reached a
breaking point
Enterprise performance management (EPM) evolved out of the basic use of spreadsheets for financial
planning and budgeting. While spreadsheets are still widely used for planning, larger and/or more so-
phisticated organizations have adopted specialized software for these purposes. The promise of EPM is
to extend the knowledge of and discipline around “the numbers” beyond the purview of finance and
into other departments across the enterprise.
Data provisioning is the process of preparing, integrating, and delivering data in the right format, at the
right time, to the users and systems for corporate planning, reporting, analytics, and more. Data provi-
sioning is a critical component to successful EPM implementations. However, it often feels like an uphill
battle – sometimes up a very steep one. BARC research consistently confirms this fact.1 Companies need
master data to define planning hierarchies and actuals to have orientation for plans. Planning figures
must also be accessible by reporting software to communicate results or to trigger further actions. But
often a seamless flow cannot be taken for granted.
Twenty years ago, vendors promised to reduce data management workload for business users. However,
data volumes and planning scope have exploded instead. Two underestimated driving forces cause
much of the pain we feel today.
• Today, data is captured at astronomical volumes, and the number of internal source systems
delivering it has exploded – and that’s not even considering external data.
• The other factor is pretty well summarized by this: “Appetite comes with eating.” If you have
better software that increases your efficiency, you end up doing more “stuff” than before. You
plan more areas (subplans), run more simulations and forecasts2, and deliver more extensive
reports to your management.
We have reached a point where we can no longer follow the current trajectory. Many struggle to inte-
grate all relevant data into a dedicated planning system. The three main drivers further reinforce the
pressure exerted.
• Companies are moving from doing predominantly financial planning (FP&A) to widening their
scope to what is called extended planning (xP&A) or integrated planning. This requires lever-
aging data from more sources beyond core financial and cost accounting systems, databases,
and enterprise resource planning (ERP) solutions. It also magnifies the challenges around data
provisioning, quality, and management.
• The second trend that requires organizations to extend the capabilities of their planning systems
is artificial intelligence (AI). Automated forecasts, predictions and simulations use machine
learning (ML), also known as “traditional AI,” which requires large amounts of data. The aggre-
gated values often used in planning lack the necessary depth and signals. AI/ML relies on de-
tailed data in wide tables, which is not the type of data assets that a typical planning system can
easily process.
1 49% of companies are planning to invest in “Data management and data integration” within the next 12 months – ranking it number
2 among all software investment priorities. Its importance to companies with heterogeneous data landscapes has increased noticeably.
“The CFO Agenda 2025”, BARC 2025
2 49 percent have increased the frequency of their planning and forecasting cycles to achieve greater planning resilience. “Resilient
Planning in Volatile Markets”, BARC 2025
Why EPM data management has reached a
breaking point
Enterprise performance management (EPM) evolved out of the basic use of spreadsheets for financial
planning and budgeting. While spreadsheets are still widely used for planning, larger and/or more so-
phisticated organizations have adopted specialized software for these purposes. The promise of EPM is
to extend the knowledge of and discipline around “the numbers” beyond the purview of finance and
into other departments across the enterprise.
Data provisioning is the process of preparing, integrating, and delivering data in the right format, at the
right time, to the users and systems for corporate planning, reporting, analytics, and more. Data provi-
sioning is a critical component to successful EPM implementations. However, it often feels like an uphill
battle – sometimes up a very steep one. BARC research consistently confirms this fact.1 Companies need
master data to define planning hierarchies and actuals to have orientation for plans. Planning figures
must also be accessible by reporting software to communicate results or to trigger further actions. But
often a seamless flow cannot be taken for granted.
Twenty years ago, vendors promised to reduce data management workload for business users. However,
data volumes and planning scope have exploded instead. Two underestimated driving forces cause
much of the pain we feel today.
• Today, data is captured at astronomical volumes, and the number of internal source systems
delivering it has exploded – and that’s not even considering external data.
• The other factor is pretty well summarized by this: “Appetite comes with eating.” If you have
better software that increases your efficiency, you end up doing more “stuff” than before. You
plan more areas (subplans), run more simulations and forecasts2, and deliver more extensive
reports to your management.
We have reached a point where we can no longer follow the current trajectory. Many struggle to inte-
grate all relevant data into a dedicated planning system. The three main drivers further reinforce the
pressure exerted.
• Companies are moving from doing predominantly financial planning (FP&A) to widening their
scope to what is called extended planning (xP&A) or integrated planning. This requires lever-
aging data from more sources beyond core financial and cost accounting systems, databases,
and enterprise resource planning (ERP) solutions. It also magnifies the challenges around data
provisioning, quality, and management.
• The second trend that requires organizations to extend the capabilities of their planning systems
is artificial intelligence (AI). Automated forecasts, predictions and simulations use machine
learning (ML), also known as “traditional AI,” which requires large amounts of data. The aggre-
gated values often used in planning lack the necessary depth and signals. AI/ML relies on de-
tailed data in wide tables, which is not the type of data assets that a typical planning system can
easily process.
1 49% of companies are planning to invest in “Data management and data integration” within the next 12 months – ranking it number
2 among all software investment priorities. Its importance to companies with heterogeneous data landscapes has increased noticeably.
“The CFO Agenda 2025”, BARC 2025
2 49 percent have increased the frequency of their planning and forecasting cycles to achieve greater planning resilience. “Resilient
Planning in Volatile Markets”, BARC 2025
4BARC Spotlight: EPM on Your Data Platform: Unlocking Flexibility & AI
• The third one is easy to guess. It’s volatility – the market dynamics that surround us all. This
requires a faster reaction time, meaning less time is allotted for adjusting models and connect-
ing new, relevant sources. Additionally, the external factors causing volatility demand that or-
ganizations to increasingly leverage external data – again more data sources with a wide variety
of formats.
The effort required for connecting to sources, transforming data, and modeling the systems increases
significantly. Unfortunately, funneling data through a data warehouse does not completely eliminate
this effort. Similarly, although AI, especially GenAI and agentic AI, can alleviate the situation somewhat,
the problem remains. AI and its variants will likely change that for many companies, but not all. Some
companies will be less inclined to use AI to improve their data management due to factors such as size,
industry, or culture.
Figure 1: What are your company’s biggest challenges in terms of performance management? (n=193).
“Boost Finance Productivity with Unified Performance Management,” BARC 2023.
• The third one is easy to guess. It’s volatility – the market dynamics that surround us all. This
requires a faster reaction time, meaning less time is allotted for adjusting models and connect-
ing new, relevant sources. Additionally, the external factors causing volatility demand that or-
ganizations to increasingly leverage external data – again more data sources with a wide variety
of formats.
The effort required for connecting to sources, transforming data, and modeling the systems increases
significantly. Unfortunately, funneling data through a data warehouse does not completely eliminate
this effort. Similarly, although AI, especially GenAI and agentic AI, can alleviate the situation somewhat,
the problem remains. AI and its variants will likely change that for many companies, but not all. Some
companies will be less inclined to use AI to improve their data management due to factors such as size,
industry, or culture.
Figure 1: What are your company’s biggest challenges in terms of performance management? (n=193).
“Boost Finance Productivity with Unified Performance Management,” BARC 2023.
5BARC Spotlight: EPM on Your Data Platform: Unlocking Flexibility & AI
This survey data from the BARC Report, “Boost Finance Productivity with Unified Performance Manage-
ment,” shows that most of the top reported challenges are connected to these issues.
If you need more proof that data management is a primary concern for finance experts, take a look at
the trends in BARC’s most recent “CPM Trend Monitor 2026” study.
“Data management is the most important trend in this year’s CPM Trend Monitor,
reflecting its critical role across companies of all sizes, industries, and regions. Treating data as a
strategic asset is now a top priority for finance leaders. High-quality, consistent, and reliable data
is essential not only for informed decision-making, driving innovation, automating processes, and
enabling technologies such as AI and ML.”
Figure 2: Importance of current CPM trends and priorities for 2026 (n= 989). “CPM Trend Monitor 2026,”
BARC and BPM Partners 2025.
The cost of data duplication in planning databases
The dominant approach today is to load data into specialized, dedicated data stores to provide the
performance, functionality, and flexibility required for enterprise-wide planning. Optimized in-memory
and multidimensional databases are the preferred technology of most leading vendors. While this ap-
proach of duplicating data has its clear advantages, there are also relevant disadvantages and limitations
to consider.
• Let’s start with the most obvious but least significant downside: Duplicating data increases stor-
age consumption. Although this was a major issue ten years ago, storage costs are now usually
insignificant compared to other costs.
• Data sprawl is the ultimate governance nightmare. How can a company efficiently and effectively
ensure security and track usage if data is stored in multiple systems? These multiple systems
n=989
This survey data from the BARC Report, “Boost Finance Productivity with Unified Performance Manage-
ment,” shows that most of the top reported challenges are connected to these issues.
If you need more proof that data management is a primary concern for finance experts, take a look at
the trends in BARC’s most recent “CPM Trend Monitor 2026” study.
“Data management is the most important trend in this year’s CPM Trend Monitor,
reflecting its critical role across companies of all sizes, industries, and regions. Treating data as a
strategic asset is now a top priority for finance leaders. High-quality, consistent, and reliable data
is essential not only for informed decision-making, driving innovation, automating processes, and
enabling technologies such as AI and ML.”
Figure 2: Importance of current CPM trends and priorities for 2026 (n= 989). “CPM Trend Monitor 2026,”
BARC and BPM Partners 2025.
The cost of data duplication in planning databases
The dominant approach today is to load data into specialized, dedicated data stores to provide the
performance, functionality, and flexibility required for enterprise-wide planning. Optimized in-memory
and multidimensional databases are the preferred technology of most leading vendors. While this ap-
proach of duplicating data has its clear advantages, there are also relevant disadvantages and limitations
to consider.
• Let’s start with the most obvious but least significant downside: Duplicating data increases stor-
age consumption. Although this was a major issue ten years ago, storage costs are now usually
insignificant compared to other costs.
• Data sprawl is the ultimate governance nightmare. How can a company efficiently and effectively
ensure security and track usage if data is stored in multiple systems? These multiple systems
n=989